Move to AWS Cloud and Maximize Cost Efficiency

Answer: B.

From the scenario, we can see that the On-Premises applications' workload is continuous & stable.

For these kinds of applications, it is easy to predict upfront capacity.

Also, since the application runs continuously, I will benefit by reserving capacity for a certain period of time.

Option A is incorrect.

The Pay-as-you-go model will be best used for workloads used for short durations & have unpredictable load.

On-demand EC2 instances will be the best fit for this purpose.

Option B is CORRECT.

Since there is continuous usage of these applications with a predictable load, it will be best for me to reserve capacity upfront (period of 1 - 3 years) that will provide a substantial discount of 30 - 50% compared to its On Demand counterparts.

Option C is incorrect.

Pay less by using more refers to volume discounts provided by AWS for increased usage.

E.g., S3 Standard provides the following storage pricing, also referred to as Tiered-Pricing.

Data Storage.

Storage Pricing.

First TB / month.

$0.025 per GB.

Next 450 TB / month.

$0.024 per GB.

Next 500 TB / month.

$0.023 per GB.

Option D is incorrect.

Pay-per-compute-time refers to the use of serverless architectures like Lambda, where you pay only for the time when the compute resources are running.

Unlike EC2 Pay-as-you-go pricing, AWS provisions resources for executing Lambda functions on the fly & removes them immediately after execution.

So there is no idle utilization time that needs to be accounted for.

Since our scenario consists of long-running applications, this option will be impractical for usage.

References:

https://aws.amazon.com/pricing/#:~:text=AWS%20offers%20you%20a%20pay,utilities%20like%20water%20and%20electricity. https://dzone.com/articles/the-cost-of-the-cloud-the-ultimate-aws-pricing-gui https://www.apptio.com/blog/aws-reserved-instances-cost-optimization/ https://d1.awsstatic.com/whitepapers/aws_pricing_overview.pdf

The economic feature that will benefit you most in this scenario is "Save when you Reserve," which is option B.

When you move your applications to the cloud, you want to make sure you're using your resources as efficiently as possible. AWS offers several pricing models, but for consistent workloads like yours, the most cost-effective option is likely to be Reserved Instances (RIs).

Reserved Instances are a way to commit to using a certain amount of compute capacity in exchange for a discount on the hourly rate. You can purchase RIs for a 1- or 3-year term, and you can choose to pay all upfront, partial upfront, or no upfront. The more you pay upfront, the bigger the discount you'll receive.

Using Reserved Instances means that you'll have a guaranteed amount of capacity available to you at all times, without having to worry about fluctuations in demand or paying for more than you need. This can result in significant cost savings compared to paying the On-Demand rate (which is essentially pay-as-you-go) over the long term.

Option A, Pay-as-you-go, means you pay only for what you use, with no upfront costs or commitments. This model can be useful if you have unpredictable workloads or if you're just starting out and want to experiment with different services.

Option C, Pay less by using more, refers to AWS's tiered pricing structure. As you use more of a particular service, you'll move up to a higher usage tier and receive a lower per-unit cost. This can be a good option for services with variable usage patterns, but it's unlikely to be the most cost-effective choice for consistent workloads.

Option D, Pay-per-compute-time, isn't a specific pricing model offered by AWS, but it could refer to the way that some services are priced, such as AWS Lambda. With Lambda, you're charged only for the time that your code is actually executing, rather than for the full duration of a server instance. This can be a cost-effective option for certain workloads, but it may not be the best choice if you need to run applications continuously.